Markerstudy Group
Machine Learning Engineer
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Job title: Machine Learning Engineer
Locations: Manchester or Haywards Heath (hybrid working)
Role Overview
Markerstudy Group are looking for a Machine Learning Engineer to help take leading-edge and novel insurance risk modelling and pricing techniques and participate in creating fully automated machine learning pipelines.
Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1 billion. Most of Markerstudy’s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.
As a Machine Learning Engineer, you will use your skills to:
- Tune machine learning methods to best leverage our state-of-the-art processing capabilities
- Deploy and maintain machine learning methods in a DevOps / MLOps based machine learning environment
- Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards
Your work will enable sustained improvements to products, prices and processes giving Markerstudy a critical advantage in the increasingly competitive insurance market by minimizing the development to deployment and monitoring stages of the ML lifecycle through automation.
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You will also be responsible for refining, tuning, deploying and maintaining machine learning methods in our machine learning pipeline by using robust test-driven development (TDD) approaches to maximise performance and robustness, and improve company performance and our customer-centric offerings across Motor, Home and Commercial Lines businesses. The successful candidate will also enjoy opportunities for leading, coaching, and mentoring more junior ML Engineers.
Key Responsibilities:
- Report and communicate with Senior Stakeholders, such as the Head of Data Science and Machine Learning and Director of Technical Underwriting
- Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software.
- Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible.
- Tune machine learning methods for optimal performance.
- Deploy and maintain machine learning methods in our machine learning pipeline using robust test-driven development (TDD) coding approaches, using the SOLID software development principles.
- Actively contribute to creating a culture of coding and data excellence
- Implement efficient solutions across a range of markets, including Private Motor, Commercial Vehicle, Bike, Taxi, and Home
- Lead and mentor junior machine learning engineers and share best practices
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Key Skills and Experience:
- Previous experience in tuning and deploying machine learning methods
- Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering
- Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc.
- Experience with deploying services in Docker and Kubernetes
- Experience in creating production grade coding and SOLID programming principles, including test-driven development (TDD) approaches
- Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL)
- Experience in source-control software, e.g., GitHub
- Proficient at communicating results in a concise manner both verbally and written
- Experience in data and model monitoring is a plus
Behaviours:
- A high level of professional/academic excellence, educated to at least a master’s level in a STEM-based or DS / ML / AI / or mathematical discipline
- Collaborative and team player
- Logical thinker with a professional and positive attitude
- Passion to innovate and improve processes
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